Store MCP Server
Enables AI agents to store and retrieve information persistently using key-value pairs with JSON file-based storage. Supports storing, retrieving, listing, deleting, and searching data across sessions.
README
Store MCP Server
A Model Context Protocol (MCP) server that enables AI agents to store and retrieve information persistently.
Project Structure
store_mcp/
├── README.md # This file
├── pyproject.toml # Project dependencies and configuration
├── src/
│ └── store_mcp/
│ ├── __init__.py # Package initialization
│ ├── server.py # Main MCP server implementation
│ └── storage.py # Storage backend (JSON/SQLite)
└── tests/
├── __init__.py
└── test_server.py # Unit tests
Features
- Store Information: Save key-value pairs or structured data
- Retrieve Information: Query stored data by key or search criteria
- List Keys: View all available stored keys
- Delete Information: Remove stored data when no longer needed
- Persistent Storage: Data persists across sessions
Installation
# Install dependencies
pip install -e .
Usage
# Run the MCP server
python -m store_mcp.server
MCP Tools
The server exposes the following tools to AI agents:
store_data: Store information with a keyretrieve_data: Retrieve information by keylist_keys: List all stored keysdelete_data: Delete stored information by keysearch_data: Search stored information by pattern or content
Configuration
MCP Client Configuration
To use this server with an MCP client (like Claude Desktop), add it to your MCP settings configuration file:
For Claude Desktop on MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
For Claude Desktop on Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"store": {
"command": "python",
"args": [
"-m",
"store_mcp.server"
],
"env": {
"PYTHONPATH": "/absolute/path/to/store_mcp/src"
}
}
}
}
Alternative using uvx (if installed via pip):
{
"mcpServers": {
"store": {
"command": "uvx",
"args": [
"--from",
"/absolute/path/to/store_mcp",
"python",
"-m",
"store_mcp.server"
]
}
}
}
Storage Configuration
The server uses a local file-based storage system (JSON) located at:
- Default:
~/.store_mcp/data.json
To use a custom storage location, modify server.py and initialize Storage with a custom path:
storage = Storage("/path/to/custom/data.json")
Environment Variables
You can set the following environment variables:
STORE_MCP_PATH: Custom path for the storage file (default:~/.store_mcp/data.json)
Example configuration with custom storage path:
{
"mcpServers": {
"store": {
"command": "python",
"args": ["-m", "store_mcp.server"],
"env": {
"PYTHONPATH": "/absolute/path/to/store_mcp/src",
"STORE_MCP_PATH": "/custom/path/to/storage.json"
}
}
}
}
Development
# Run tests
pytest tests/
Requirements
- Python 3.10+
- mcp library
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